It has been widely recognized that Multi-view Video Coding is a key technology that serves a wide variety of applications, including free-viewpoint and three-dimensional (3D) video applications, home entertainment and surveillance. In addition, depth data may be associated with each view. Depth data is generally essential for view synthesis. In those multi-view applications, the amount of video and depth data involved is typically enormous. Thus, there exists at least the desire for a framework that helps improve the coding efficiency of current video coding solutions performing simulcast of independent views.
A multi-view video source includes multiple views of the same scene. As a result, there typically exists a high degree of correlation between the multiple view images. Therefore, view redundancy can be exploited in addition to temporal redundancy. View redundancy can be exploited by, for example, performing view prediction across the different views.
In a practical scenario, 3DV systems may encode partial views and the other views will be reconstructed using view synthesis. The residual signal for the skipped views may be sent if higher quality is required. Moreover, the synthesized pictures can serve as references to encode the subsequent pictures.